Package: clustvarsel
Type: Package
Version: 2.1
Date: 2014-10-15
Title: Variable Selection for Model-Based Clustering
Description: A function which implements variable selection methodology for model-based clustering which allows to find the (locally) optimal subset of variables  in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting MCLUST models. By default the algorithm uses a sequential search, but parallelization is also available.
Author: Nema Dean, Adrian E. Raftery, and Luca Scrucca
Maintainer: Luca Scrucca <luca@stat.unipg.it>
Depends: R (>= 2.15), mclust (>= 4.4), BMA (>= 3.16), foreach,
        iterators
Suggests: MASS, parallel, doParallel
License: GPL (>= 2)
Repository: CRAN
ByteCompile: true
LazyLoad: yes
Packaged: 2014-10-15 08:04:12 UTC; luca
NeedsCompilation: no
Date/Publication: 2014-10-15 10:41:07
Built: R 3.1.1; ; 2014-10-16 11:27:55 UTC; unix
